1. Field of the Invention
This invention relates generally to digital systems for transforming color images from one medium of expression to another and specifically to a digital system for transforming color images from an original form to a device-dependent form that appears to a human observer as a subjectively-accurate depiction of the original image.
2. Discussion of the Related Art
The actual or perceived quality of an imaging system depends primarily on the degree to which the output image appears to match the input image in the subjective opinion of the viewer. In a color image display or reproduction system, where an input color image is reproduced or copied as an output color image, the subjective fidelity between input and output images includes the color content of the image as well as the achromatic subject matter. That is, the various shades and intensities of the different colors in an image must appear to have the same relationship to one another as in the original image. Ideally, the colors of the output image are subjectively indistinguishable from the input image colors.
To ensure proper display of the output image, an imaging system must provide for "gamut mapping" of the original image to the limited range ("gamut") of colors available in the output display or reproduction device. For any particular image reproduction system, the input gamut and output gamut are not likely to be coextensive and generally exhibit substantial non-overlapping regions.
In certain color imaging systems, digital images are stored in "device-independent" form, which implies that the stored image was digitized with an image-sensing device possessed of a gamut that embraces a substantial portion of the entire human-sensitive visual color space. In such form, the image file includes image point ("pixel") data values representing image colors as perceived by a human observer. When the image is displayed or printed, the image pixel colors must be translated to the proper combination of output device parameters, such as beam currents (for CRT displays), ink quantities (for ink-jet printers), and the like. It is generally quite likely that some of the image colors found in the device-independent color space are not available in the output display. The range of colors available from an output display device is herein denominated the "device gamut". The process of translating device-independent image colors to device-dependent image colors is herein denominated "gamut mapping", which includes the process of substituting colors inside the device gamut ("in-gamut") for original colors falling outside of the device gamut ("out-gamut"). Much gamut mapping can be accomplished using "point processes," which are procedures that treat each pixel independently of all other image pixels. Such procedures are herein denominated "point gamut mapping" procedures. "Neighborhood gamut mapping" herein denominates similar procedures that consider nearby pixel colors when mapping a pixel to the device gamut.
Point gamut mapping procedures known in the art (see Gentile, R. S., et al., "A Comparison of Techniques for Color Gamut Mismatch Compensation", Journal of Imaging Technology, vol. 18, no. 5, Oct., 1990, pp. 176-181) include both clipping and compression techniques. Clipping techniques are those which map unrealizable input image colors to the border of the realizable output gamut. Compression techniques perform local color space scaling to map a local portion of the input image color space into the realizable output device gamut. With both techniques, each particular input color is always translated to a particular output color (one-to-one mapping) regardless of either the location of the pixel within the image or the pixel neighborhood color conditions.
Practitioners in the art have proposed many improvements to point gamut mapping procedures. Much of this art is directed to transferring video images to hard copy. For instance, in U.S. Pat. No. 4,670,780, McManus et al. disclose a method for matching hard copy colors to display colors for register-dot ink-jet copiers. McManus et al. teach a point-process mapping scheme that compresses the out-of-gamut colors to the gamut edges. Similarly, in U.S. Pat. No. 4,751,535, Myers discloses a technique for matching CRT display colors in a color print by transforming the CRT image coordinates through a linear mixing space such as a CIE Cartesian color space. Similar techniques are disclosed by Abdulwahab et al. in U.S. Pat. No. 4,839,721, by Walowit in U.S. Pat. No. 4,941,038, and by Chan in U.S. Pat. No. 5,107,332. Chan further teaches a method and system for continuously correcting for errors in color output of a color printer arising from changes in the system between input image and output print. Also, in U.S. Pat. No. 5,185,661, Ng discloses a system that corrects for color interpretation errors in the scanning color filter set before mapping the digital color image to a color printer gamut. Ng prefers a non-linear chroma compression scheme that retains some of the color distinctions among the out-gamut pixels.
In U.S. Pat. No. 4,812,902, Fuchsberger describes a system that compresses the image chrominance component on a pixel-by-pixel basis to reduce the image to an output gamut. In U.S. Pat. No. 4,812,903, Wagensonner et al. describe a system that selectively enhances contrast through the use of spatial-filtering and attempt to compensate for subjective changes in chroma magnitude by adjusting the chrominance signals according to the ratio of new to old luminance. Wagensonner et al. use a clipped chrominance compression scheme to reduce image gamut and employ spatial filtering only to permit selective enhancement of high spatial frequency luminance components. They neither consider nor suggest the use of spatial filtering to compensate for the subjective visual effects of chrominance compression. In U.S. Pat. No. 4,831,434, Fuchsberger also scales chrominance by the ratio of changes in image luminance employed for contrast enhancement in attempting to compensate for the subjective chrominance effects of the luminance changes.
Other practitioners have suggested improved methods for color-correction during color photograph negative processing and printing. For instance, in U.S. Pat. No. 4,825,297, Fuchsberger et al. propose a system for contrast-amplification that does not construct an explicit linear color-space image representation but instead processes the original image in some unspecified form. Fuchsberger et al. pass the image through both a low-pass filter and a high-pass filter, amplifying the high-pass filter output with a non-linear amplifier that compresses the dynamic range of the image signal and then passing the result through a non-linear point process before combining the result with the low-pass filter output. Their desired contrast-enhancement arises from the resulting low spatial bandwidth in dark image regions and high spatial bandwidth in bright image regions. Fuchsberger et al. neither consider nor suggest application of their method to the chrominance elements of an image. In U.S. Pat. No. 4,933,754, Reed et al. discloses a system for adjusting the contrast (luminance) of a photographic print by scanning the negative and digitizing the image for use in selectively controlling a matrix of liquid crystal elements interposed between a lamp and the developed film negative.
Other practitioners have suggested image gamut mapping improvements applicable to video-to-video display conversions. For instance, in U.S. Pat. No. 4,721,951, Holler discloses a fundamental interactive color selection system that permits an interactive user to make changes in gamut-mapping parameters and observe the results immediately on side-by-side image displays. Similarly, in U.S. Pat. No. 5,012,333, Lee et al. disclose an interactive method for dynamic range adjustment applicable to printing digital color images. Lee et al. teach limiting contrast (luminance) changes to the low-spatial frequency components of the image while preserving or enhancing the contrast (luminance) in high-spatial frequency image components. The user may interact with the system by adjusting gamut-mapping curves and comparing input and output images on side-by-side displays.
Also, in U.S. Pat. No. 5,138,303, Rupel discloses a dynamic-range compression system for mapping a higher number of intensity levels from a digital image to a lower number of intensity levels supported in an output image display by dithering the apparent intensity within a pixel neighborhood. Activating various numbers of neighborhood pixels gives the illusion of more display intensity levels for a given color than are supported by the pixel drivers.
All of the above point-process gamut-mapping techniques rely to some extent on either clipping or compression of chrominance intensity to force image pixels into the output device gamut. In the above-cited Lee et al. reference (U.S. Pat. No. 5,012,333, entirely incorporated herein by this reference), Lee et al. suggest limiting the gamut-mapping adjustment of luminance to the low spatial frequency components because human vision is less sensitive to luminance changes at the lower spatial frequencies (see, e.g., Davidson, M. "Perturbation Approach to Spatial Brightness Interaction in Human Vision," Journal of the Optical Society of America, vol. 58, No. 9, Sep. 1968, pp. 1300-1308; and van der Horst, G. J. C. et al., "Transfer of Spatial Chromaticity-Contrast at Threshold in the Human Eye," Journal of the Optical Society of America, Vol. 57, No. 10, Oct. 1967, pp. 1260-1266). However, Lee neither considers nor suggests optimizing his neighborhood gamut-mapping technique to minimize the subjective chrominance distortion resulting from the clipping or compression employed to fit the image to a gamut. Lee et al. adjust the contrast (luminance) of the low-frequency image components only, preserving or enhancing contrast of the high-frequency image components. By low-pass filtering, the luminance component of the image and subtracting a result from the luminance component to yield a high-pass filtered version of the luminance component of the image, Lee et al. essentially drive the luminance values of the final image toward middle gray while preserving in undiminished form the high-frequency changes in luminance (image features). Lee et al. neither consider nor suggest using the human insensitivity to low-frequency luminance changes to avoid visible chrominance distortion in the low-frequency region. Although the human spatial frequency response to chrominance was shown by van der Horst et al. to fall rapidly with increasing spatial frequency, until now, no practitioner has suggested gamut-mapping system improvements designed to exploit this human visual characteristic. There is still a clearly-felt need in the art for solutions to the unresolved problems and deficiencies in color image gamut-mapping technology. Some of these heretofore unresolved problems and deficiencies are solved by this invention in the manner described below.